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Record W4409891858 · doi:10.1177/11771801251334914

Sexual and gender diversity in a Métis community: challenging stigma and celebrating resilience

2025· article· en· W4409891858 on OpenAlexafffundabout
Allison Reeves, Rachel Landy

Bibliographic record

VenueAlterNative An International Journal of Indigenous Peoples · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Identity, and Health
Canadian institutionsDalhousie UniversityUniversity of GuelphUniversity of Guelph-Humber
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsStigma (botany)Resilience (materials science)Diversity (politics)PsychologySociologyGender studiesAnthropologyPsychiatryPhysics

Abstract

fetched live from OpenAlex

Shining Mountains Living Community Services in Red Deer, Alberta, Canada, provides a range of social services for Indigenous Peoples in the area, particularly Métis (an Indigenous people of Canada), who are struggling with sexual health vulnerabilities. Under the direction of a Métis Wellness Advisory Council at Shining Mountains, this study sought to understand how stigma and discrimination affect sexually diverse and gender-diverse Métis community members. Grounded in qualitative interviews and Métis methods including sharing circles and visual arts, this study looked at experiences of stigma, resilience, and healing for Key Informants including sexual or gender-diverse Métis Peoples. This article details findings from eight Key Informant interviews and discusses major themes related to Layers of Stigma, Métis Identity and Teachings, and Resilience and Healing. Conclusions offer directions for mental health service development and community healing.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.724
Threshold uncertainty score0.549

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0270.017
Scholarly communication0.0040.002
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.061
GPT teacher head0.372
Teacher spread0.311 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes3
Has abstractyes

Explore more

Same venueAlterNative An International Journal of Indigenous PeoplesSame topicMigration, Identity, and HealthFrench-language works237,207